E-procurement is a key area of e-business and supply chain management in which catalogs and reverse auctions have been widely used (Anderson and Frohlich, 2001; Jap, 2003). On average, about 70% of corporate revenue is spent on purchasing; savings of 5% translate into hundreds of millions of dollars (Peleg, 2003; Wagner and Schwab, 2004). Reverse auctions have been shown to achieve average gross savings of 15-20 percent (Cohn, 2000.)
There are two kinds of auctions: single-shot and iterative. Iterative auctions, which allow bidders to revise their bids, are becoming prevalent in procurement (Parkes and Kalagnanam, 2005). One of the limitations of auctions is that they use a single attribute (i.e., price), which leads to inefficient agreements (Strecker and Seifert, 2004) and is not practical in many business transactions (Teich, Wallenius et al., 2004). A survey by Ferrin and Plank (2002) found that over 90% of purchasing managers based their decisions on both price and non-price variables (e.g., durability, service, lead-time and trust).
Two types of iterative auctions are possible: synchronous and asynchronous. An auction is synchronous if every seller makes at most one bid in each round. The auction mechanism—acting on behalf of the buyer—selects the best bid as the reference bid and presents it to the sellers. The sellers use the reference bid to construct their bids in the next round bid. In addition, the buyer may provide other information to help sellers construct their bids. Asynchronous auctions allow sellers to bid at any time until the auction's deadline. The most recent best bid is shown to the bidders. If a better bid is submitted then it replaces the previous best bid.
Auction design has traditionally focused on the construction of rules which govern the behavior of auction participants so that their auctions lead to a desired market outcome. The outcome is the final allocation of the goods and money. The desired aspect of the outcome is the auction initiator (the buyer in our case), profit or revenue maximization, or it is the creation of an efficient market (Kittsteiner and Ockenfels, 2006). The rules specify the winner determination formula, auction duration and the type of deadline (extendible or fixed), types of bids (sealed or open), and so on.
In synchronous iterative single-attribute auctions the rules determine whether: (1) all bids are open and posted so that they are visible to all bidders; (2) only some bids are open and visible; or (3) only the best bid made in a given round is open and visible. Either of these options is sufficient for the bidders to decide on bidding in the next round. Therefore, the rule defining an acceptable bid is simple—every submitted bid must exceed the last posted bid. This rule assures that the time-order of bids is the same as the profit-order for the buyer, that is, later bids are better than earlier. The concept “better than” is easily operationalized by the explicit auction criterion, which is the single attribute.
Procurement of more complex goods and services often requires consideration of multiple attributes (e.g., total costs of ownership components, quality, risk, and schedules). Survey results show that most procurement officers make purchasing decisions based on the total costs of ownership (Ferrin and Plank, 2002; Talluri and Ragatz, 2004)
Multi-attribute auctions cannot have a “better than” rule because there is no single auction criterion that is: (1) explicit and known to all participants; and (2) completely describes bids so that they can be ordered. Ways to overcome the lack of an explicit criterion include: (1) evaluation and selection of multi-attribute bids only after they are submitted (U.S. Pat. No. 7,200,570 B1, 2007); (2) pre-selection of bidders so that only bidders who are known to meet the additional criteria are included; (3) giving incumbents an advantage because their qualifications are known; and (4) the use of disclaimers such as “the lowest bid may not be awarded the contract” (Bichler and Kalagnanam, 2005; Engelbrecht-Wiggans, Haruvy et al., 2007; Schoenherr and Mabert, 2007). In these types of auctions either the selection or bidding process are modified so that a single-attribute auction can be used.
The results of such auction modification are mixed. Post-auction evaluation either requires that bidders know the buyer's evaluation function or renders multi-round and synchronous auction inadmissible because the bidders are unable improve their bids. These auctions may also lead to collusion and selection of inferior offers (Elmaghraby, 2004; Katok and Wambach, 2011). In some situations the process becomes an auction in name only, as is the case with an auction in which neither the winner nor any other participant is awarded the contract (Engelbrecht-Wiggans, Haruvy et al., 2007).
Another, seemingly simple approach is to give bidders all information which the buyer uses in order to analyze and compare bids (Chen-Ritzo, Harrison et al., 2005; Karakaya and Köksalan, 2011; Srinath, Singh et al., 2011). This requires specification of the buyer's evaluation function which is defined on the good or service attributes. A number of method used to construct such a function has been proposed (U.S. Pat. No. 7,584,124 B2, 2009) (see also, Bichler, 2000; Beil and Wein, 2003; Bellosta, Kornman et al., 2008).
This somewhat complicates the computation because the bidders need to optimize using both their own and the buyer's information (e.g., utility or a scoring function). It may also encourage the buyer to engage in strategic misrepresentation and announce a utility function with the aim of pushing the sellers to make favorable bids (Burmeister, Ihde et al., 2002).
This approach is, however, unacceptable when buyers do not want to disclose their preferences for strategic, competitive, or other reasons (Burmeister, Ihde et al., 2002; Parkes and Kalagnanam, 2005). In the context of multi-attribute bidding, this means that the bidders do not know how to bid; they cannot make tradeoffs that take the buyer's preferences into account and they may misinterpret the buyer's preferential directions. The bidders may make strong assumptions about the buyer's utility and bid accordingly. This may be acceptable if their knowledge of the buyer's preferences is accurate and the buyer accepts an inefficient winning bid.
Another option has been proposed by economists. This option rests on the assumption that all attributes can be expressed in monetary terms so that only two items need to be considered: (1) price, and (2) all remaining and monetized attributes, which typically represent costs—for the sellers and value (income)—for the buyer. When an assumption is added that these two terms are monotonic and the buyer compares bids using the difference between value and price, then the sellers can partially determine the buyer's preferential order of the alternatives.
The attribute monetization methods have been widely implemented and tested (e.g., Che, 1993; Strecker and Seifert, 2004; Bichler and Kalagnanam, 2005), and they are considered a standard in the auction literature (Parkes and Kalagnanam, 2005). These methods, based on two-attribute monetary value functions, are appealing because they allow buyers and sellers to integrate and trade off all attributes included in the cost function (Strecker and Seifert, 2004). On one hand, the bidder may choose a bid among his/her indifferent alternatives (i.e., different bids which yield the same utility for this bidder) that yields the highest utility to the buyer; on the other hand, the owner evaluates bids based on the total utility of bids and chooses the highest one. The limitation of this method is the underlying assumption that all attributes can be measured with money. The assumption is questionable, if one considers such attributes as trust, brand, or color.
The design of auction mechanisms that rely on attribute monetization involves the construction of rules that help the sellers to make progressive bids; i.e., bids which are better for the buyer than the bids made earlier. The information conveyed to the sellers is about the buyer's preferences and it is either complete or incomplete but sufficient to assure the auction convergence. A different approach has been proposed by Teich, Wallenius et al. (1999) in which the sellers are informed about a path in the space of alternatives. However, the buyer's preferences could consist of confidential information that the buyer would prefer not revealing to the sellers, thus discouraging the buyer from participating.
Other work that has taken place in the area of providing means for multi-attribute reverse auctions is reflected in the patents in this area.
U.S. Pat. No. 6,112,189, 2000 describes a system that supports multi-attribute negotiations among multiple parties. The parties exchange alternatives (bids) and provide the secure system with their satisfaction functions. The system calculates overall joint satisfaction and selects an alternative that maximizes joint satisfaction. This approach replaces market system with a central unit (controller) that has all required information and uses it to provide all participants with a single “best for all” solution.
U.S. Pat. No. 5,924,082 describes a method for the determination of a multi-attribute (multi-category) quality-of-service agreement. This as well as the U.S. Pat. No. 7,200,570 describes a single-step procedures so that market participants (sellers) cannot propose alternative and improved bids.
U.S. Pat. No. 7,373,325 describes a method for performing automated reverse auctions on an electronic network. The method modifies the auction with n bidders to n bilateral negotiations; in each the buyer negotiates with one seller. The process requires the buyer's active involvement and replaces an auction market mechanism with multiple bilateral negotiations.
U.S. Pat. No. 7,406,443 describes multi-dimensional trading method which requires double-auction system in which sellers submit at least four-attribute (dimensions) bids. These bids are matched to requests; if no match on all dimensions is obtained matching on fewer dimensions is undertaken. The process does not allow for auctions with fewer than four attributes, does not allow for trade-offs and requires the presence of multiple buyers.
U.S. Pat. No. 7,475,034 describes a process for the specification of an auction methodology for based on the auction scope, type of interaction, control, pricing and closing rules. This process does not address multi-attribute aspects of the goods or services and heterogeneity of the bidders.
U.S. Pat. No. 7,877,293 B2 (2011) describes a pull system that allows buyers of bundled services to compare offers. The comparison is based on multiple-attribute decision support mechanism which aggregates attribute values and constructs ratings for the bundles. The method focuses on the buyer and it does not provide information and bidding directions that would facilitate bid construction.
U.S. Pat. No. 7,958,013 B2 (2011) describes a methodology and system for a fully automated buyer's auction in which both the buyer and the sellers have near-perfect information about one another, including information about the buyer's preferences and offers made by the competing sellers. Although the information requirement is not complete, but near-perfect, it does not allow for buyers' auctions when the buyers do not want or cannot disclose their own preferences and the sellers do not have information about each other.
U.S. Pat. No. 8,112,320 B2 (2012) describes a method for multiattribute web content auctions. The method allows for the submission bids that include non-price attributes, which are converted to price through the use of a willingness-to-pay function. This function is based on the auction knowledge of the bid-maker. The bid-maker receives price for the bid which may be used to revise the bid. The application of this method is narrow and the underlying assumption is that the buyer can construct a willingness-to-pay function for each buyer and that each bidder can construct a bid that will yield a different price value.